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相关概念视频

Correlation and Regression00:53

Correlation and Regression

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In statistics, correlation describes the degree of association between two variables. In the subfield of linear regression, correlation is mathematically expressed by the correlation coefficient, which describes the strength and direction of the relationship between two variables. The coefficient is symbolically represented by 'r' and ranges from -1 to +1. A positive value indicates a positive correlation where the two variables move in the same direction. A negative value suggests a...
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Receiver Operating Characteristic Plot01:15

Receiver Operating Characteristic Plot

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A ROC (Receiver Operating Characteristic) plot is a graphical tool used to assess the performance of a binary classification model by illustrating the trade-off between sensitivity (true positive rate) and specificity (false positive rate). By plotting sensitivity against 1 - specificity across various threshold settings, the ROC curve shows how well the model distinguishes between classes, with a curve closer to the top-left corner indicating a more accurate model. The area under the ROC curve...
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Relative Risk01:12

Relative Risk

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Relative risk (RR) is a statistical measure commonly used in epidemiology to compare the likelihood of a particular event occurring between two groups. This metric is important for evaluating the relationship between exposure to a specific risk factor and the probability of a particular outcome. It plays a crucial role in medical research, public health studies, and risk assessment. Relative risk quantifies how much more (or less) likely an event is to occur in an exposed group compared to an...
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Correlation01:09

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In statistics, two variables are said to be correlated if the values of one variable are associated with the other variable. Depending on the relationship between two variables, correlation can be of three types– positive correlation, negative correlation, and zero correlation.
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Prediction Intervals01:03

Prediction Intervals

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The interval estimate of any variable is known as the prediction interval. It helps decide if a point estimate is dependable.
However, the point estimate is most likely not the exact value of the population parameter, but close to it. After calculating point estimates, we construct interval estimates, called confidence intervals or prediction intervals. This prediction interval comprises a range of values unlike the point estimate and is a better predictor of the observed sample value, y. 
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Correlation means that there is a relationship between two or more variables (such as ice cream consumption and crime), but this relationship does not necessarily imply cause and effect. When two variables are correlated, it simply means that as one variable changes, so does the other. We can measure correlation by calculating a statistic known as a correlation coefficient. A correlation coefficient is a number from -1 to +1 that indicates the strength and direction of the relationship between...
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相关实验视频

Updated: Jan 9, 2026

Using Human Differentially Expressed Gene Lists to Perform Downstream Pathway Enrichment Analysis and Target Prioritization
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Published on: October 3, 2025

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概率临床目标定义与最近邻对应关系.

L Rivetti1,2, G Buti2, L Amoudruz3

  • 1Faculty of Mathematics and Physics, University of Ljubljana, Ljubljana, Slovenia.

Physics in medicine and biology
|December 9, 2025
PubMed
概括

这项研究引入了新的随机模型来估计微观瘤存在的概率,改善了放射治疗中的临床目标体积划分. 这些模型使用空间相关性来更好地捕捉视下疾病的传播.

关键词:
临床目标地图的临床目标地图微观瘤的存在微观的瘤扩散了.可能性的CTV定义.概率的目标定义概率的目标定义空间相关性建模空间相关性建模随机瘤建模 随机瘤模型

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科学领域:

  • 辐射疗法 辐射疗法
  • 医疗成像医学成像
  • 计算生物学 计算生物学

背景情况:

  • 放射治疗中的临床目标体积 (CTV) 划分受到医疗图像上的微观疾病不可见性的限制.
  • 目前的指导方针提出了CTV的概率解释,但缺乏计算微观瘤存在 (MTP) 概率的方法.
  • 这项研究解决了概率MTP估计中的差距.

研究的目的:

  • 开发新的随机模型,以估计微观瘤存在 (MTP) 的概率.
  • 将voxel社区内的本地空间相关性纳入,以改进MTP估计.
  • 为概率性CTV定义提供统计上一致的框架.

主要方法:

  • 开发了两种第一原则的随机模型:恒定边际概率 (CMP) 和可变边际概率 (VMP).
  • CMP模型假设统一的MTP,适用于没有从总瘤体积 (GTV) 辐射依赖的瘤.
  • VMP模型结合了辐射依赖,模拟与GTV距离的距离下降MTP.

主要成果:

  • 两种CMP和VMP模型都准确地复制了MTP存在分数.
  • CMP模型估计前列腺癌中MTP的0.03边际概率.
  • VMP模型复制了乳腺和肺癌中的放射性瘤岛屿分布,平均绝对误差低.

结论:

  • 拟议的随机模型为概率CTV划分提供了一个统计学上一致的框架.
  • 这些模型通过结合局部声母相关性来增强对微观疾病传播的理解.
  • 这些模型提供了一种新的方法来解决放射治疗规划中的不确定性.